Simulated and recorded responses of mouse retinal bipolar cells to the chirp stimulus

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README.md

Data: Removing Inter-Experimental Variability from Functional Data in Systems Neuroscience

This repository hosts the data of Gonschorek, Höfling et al. (2021), Removing Inter-Experimental Variability from Functional Data in Systems Neuroscience, NeurIPS 2021. The corresponding code for the implementation can be found on GitHub.

The files contain the following data and information:

  • bio/bc_dataset_A (pickle):

    • This file contains the preprocessed bipolar cell data in response to the local and full-field chirp, their IPL (inner plexiform layer) depths and cell type labels obtained from Franke, Berens et al. (2017), Inhibition decorrelates visual feature representation in the inner retina, Nature. This dataset is licensed under the CC0 1.0 Universal (CC0 1.0) Public Domain Dedication and can be downloaded in full (incl. raw data) at datadryad
  • bio/bc_dataset_B (pickle)

    • This file contains the preprocessed bipolar cell data in response to the local and full-field chirp and their IPL depths obtained from Zhao, Klindt et al. (2020), The temporal structure of the inner retina at a single glance, Scientific Reports.
  • ipl/BC_Profiles_Helmstaedter (txt)

    • This file contains electron-microscopy (EM) data of axonal stratification profiles of bipolar cell types.
    • array of shape 400x14, array[d, t] = p(IPL depth = d|BC type = t)
  • ipl/ipl (mat)

    • Matlab file containing a dictionary with keys "d" and "prior"; d: 400x1 array, IPL depth samples; prior: 400 x 14 array, with array[d, t] = p(BC type = t|IPL depth = d).
  • silico/sim_dataset (pickle)

datacite.yml
Title Simulated and recorded responses of mouse retinal bipolar cells to the chirp stimulus
Authors Gonschorek,Dominic;University of Tübingen
Höfling,Larissa;University of Tübingen
Szatko,Klaudia;University of Tübingen
Franke,Katrin;University of Tübingen
Schubert,Timm;University of Tübingen
Dunn,Benjamin;Norwegian University of Science and Technology
Berens,Philipp;University of Tübingen
Klindt,David;University of Tübingen
Euler,Thomas;University of Tübingen
Description Simulated and recorded responses of mouse retinal bipolar cells to the chirp stimulus
License Creative Commons CC BY-NC-SA (https://creativecommons.org/licenses/by-nc-sa/4.0/)
References Removing Inter-Experimental Variability from Functional Data in Systems Neuroscience (2021) Dominic Gonschorek, Larissa Hoefling, Klaudia P Szatko, Katrin Franke, Timm Schubert, Benjamin Dunn, Philipp Berens, David A Klindt, Thomas Euler bioRxiv 2021.10.29.466492; doi: https://doi.org/10.1101/2021.10.29.466492 [doi:10.1101/2021.10.29.466492 ] (IsSupplementTo)
Franke, K., Berens, P., Schubert, T., Bethge, M., Euler, T., & Baden, T. (2017). Inhibition decorrelates visual feature representations in the inner retina. Nature, 542(7642), 439–444. https://doi.org/10.1038/nature21394 [10.1038/nature21394] (IsSupplementTo)
Zhao, Z., Klindt, D. A., Maia Chagas, A., Szatko, K. P., Rogerson, L., Protti, D. A., … Euler, T. (2020). The temporal structure of the inner retina at a single glance. Scientific Reports, 10(1), 4399. https://doi.org/10.1038/s41598-020-60214-z [10.1038/s41598-020-60214-z] (IsSupplementTo)
Helmstaedter, M., Briggman, K. L., Turaga, S. C., Jain, V., Seung, H. S., & Denk, W. (2013). Connectomic reconstruction of the inner plexiform layer in the mouse retina. Nature, 500(7461), 168–174. https://doi.org/10.1038/nature12346 [10.1038/nature12346] (IsDescribedBy)
Behrens, C., Schubert, T., Haverkamp, S., Euler, T., & Berens, P. (2016). Connectivity map of bipolar cells and photoreceptors in the mouse retina. ELife, 5(NOVEMBER2016), 1–20. https://doi.org/10.7554/eLife.20041 [10.7554/eLife.20041] (IsDescribedBy)
Funding DFG, 335549539/GRK2381
DFG, 276693517/CRC1233
DFG, Machine Learning Cluster of Excellence, EXC number 2064/1 - Project #390727645
BMBF, Tübingen AI Center, FKZ: 01IS18039A
Research Council of Norway, 90532703/FRIPRO
Keywords neuroscience
retina
bipolar cells
two-photon microscopy
synthetic data
inter-experimental variability
Resource Type Dataset